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Darrell W. Gunter  Collexis an Elsevier Company June 24, 2010 "How semantic technology enhances the productivity of scientific researchers."
Our Agenda For Today ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Facts 1,2,3 The Author is under great pressure!
Collexis Fingerprint Engine Collexis Technology KnowledgeBase Text Fingerprint
Collexis Knowledge Engine 7.0 Tokenizer Normalizer Abbreviation expansion Dehyphenation Language detection Coordination  expansion Part-of-Speech tagging Entity recognition  based on regular expressions Noun phrase detection Concept finding Part-of-speech  based disambiguation of thesaurus concepts Exclude known idioms  Fingerprint aggregation
Collexis Knowledge Engine 7.0 ,[object Object],[object Object]
Collexis – selected references American Institute of Physics Stanford University Asklepios Kliniken Johnson & Johnson Johns Hopkins University University of California, San Franciscio Dana Farber Cancer Institute Harvard University National Institutes of Health Mayo Clinic California Institute for Quantitative Biosciences (QB3), The Wellcome Trust Albert Einstein College of Medicine
Explore instead of Searching!
Creating expert profiles from documents using semantic technologies ,[object Object]
BiomedExperts – more than 300,000+ registered users  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 
[object Object]
[object Object],[object Object],[object Object]
 
 
Johns Hopkins: The Issue! Connecting Experts ,[object Object],[object Object],[object Object],[object Object]
 
 
 
 
Same Application for the NIH
Asklepios Facts and  Figures ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Optimize Workflows  (e.g. Avoid interruptions caused by knowledge search, retrieval, and application)  Distribute  Expert Knowledge  (across multiple locations, time zones, medical conditions) Guide Workflows (e.g. Care Plans, Expert-Task Context Allocation) Help Asklepios to know “what Asklepios knows” Stimulate new  Knowledge Acquisition Usage Models Why Knowledge Management?
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Use Case 1 – Expert profiles
Asklepios Research Profiles
Expert Profile of Prof. Grifka
Make Internal Expertise available!
Help Asklepios to know “what Asklepios knows” Virtualize expertise!
Provide a single point of search for all relevant content from publishers! Link internal expertise / experience and external knowledge sources!
[object Object],[object Object],[object Object],[object Object],Use Case 4  - External Resources and Internal Experience Use Case 4  - External Resources and Internal Experience
Search - Cisplatin shows the relevant publications from Springer, Elsevier, Thieme, OVID and other publishers Asklepios Intelligent Digital Library
[object Object],[object Object],[object Object],Link External Knowledge and  Internal Expertise
Key Issues in STM Industry ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Challenge for STM Publishers ,[object Object],[object Object],[object Object],[object Object],[object Object]
 
 
 
 
Key Benefits Reviewer Finder ,[object Object],[object Object],[object Object],[object Object],[object Object]
The effectiveness of Semantic Technology ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Thank you for your attention! ,[object Object],[object Object]

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How Semantic Technology Helps Researchers

  • 1. Darrell W. Gunter Collexis an Elsevier Company June 24, 2010 "How semantic technology enhances the productivity of scientific researchers."
  • 2.
  • 3. The Facts 1,2,3 The Author is under great pressure!
  • 4. Collexis Fingerprint Engine Collexis Technology KnowledgeBase Text Fingerprint
  • 5. Collexis Knowledge Engine 7.0 Tokenizer Normalizer Abbreviation expansion Dehyphenation Language detection Coordination expansion Part-of-Speech tagging Entity recognition based on regular expressions Noun phrase detection Concept finding Part-of-speech based disambiguation of thesaurus concepts Exclude known idioms Fingerprint aggregation
  • 6.
  • 7. Collexis – selected references American Institute of Physics Stanford University Asklepios Kliniken Johnson & Johnson Johns Hopkins University University of California, San Franciscio Dana Farber Cancer Institute Harvard University National Institutes of Health Mayo Clinic California Institute for Quantitative Biosciences (QB3), The Wellcome Trust Albert Einstein College of Medicine
  • 8. Explore instead of Searching!
  • 9.
  • 10.
  • 11.  
  • 12.
  • 13.
  • 14.  
  • 15.  
  • 16.
  • 17.  
  • 18.  
  • 19.  
  • 20.  
  • 22.
  • 23. Optimize Workflows (e.g. Avoid interruptions caused by knowledge search, retrieval, and application) Distribute Expert Knowledge (across multiple locations, time zones, medical conditions) Guide Workflows (e.g. Care Plans, Expert-Task Context Allocation) Help Asklepios to know “what Asklepios knows” Stimulate new Knowledge Acquisition Usage Models Why Knowledge Management?
  • 24.
  • 26. Expert Profile of Prof. Grifka
  • 28. Help Asklepios to know “what Asklepios knows” Virtualize expertise!
  • 29. Provide a single point of search for all relevant content from publishers! Link internal expertise / experience and external knowledge sources!
  • 30.
  • 31. Search - Cisplatin shows the relevant publications from Springer, Elsevier, Thieme, OVID and other publishers Asklepios Intelligent Digital Library
  • 32.
  • 33.
  • 34.
  • 35.  
  • 36.  
  • 37.  
  • 38.  
  • 39.
  • 40.
  • 41.

Editor's Notes

  1. STM Facts Over the last 12 years, the STM industry has loaded up 90% of the 23,000 journal titles. These titles generate in access of 800,000 articles per year for an estimated author community of 5.5 million worldwide researchers. It is estimated that it takes an author 90 – 100 hours to prepare a scientific article and it will take 2 – 3 reviewers 3 – 6 hours to conduct their peer review of a single article. Considering the time it takes the author to write their scientific article, consider the daunting task of the researcher to stay up on the ever growing number of scientific articles., their time is seriously being challenged. Mark Ware’s 2006 paper on the STM industry reported that size of single journal grew from 83 to 154 articles. The length of the average article grew from 7.4 to 12.4 pages and the total pages of the journal grew to 2,216 from 820 pages. A whopping 270%. Considering these statistics are a few years old and the trend is increasing each year, we know that the researcher’s burden becomes more substantial each year. Just as challenging is the academic library’s challenge to manage their collection within their budget. Unfortunately the average publisher journal price increase is always higher than the average library’s budget for serials and monographs. While the publishing community have brought great value to the research community by providing backfiles at a very reasonable cost and providing them access to their entire library of titles. The fact remains that the library’s budget and the publisher’s subscription price increases have been and will remain in conflict with each other.